Lead Data Scientist

Job Responsibilities:

• Lead all stages of data preparation, analytics & AI product development life cycle: from problem identification, conceptualization, prioritization to solution development and delivery. Contribute to hands-on development of data & analytics solutions.
• Collaborate with business and technology partners to co-create solutions, work on human-centered design, frictionless services, and meaningful engagement.
• Deliver products and solutions in a timely, proactive, and entrepreneurial manner. Accelerate solution delivery using re-usable frameworks, prototypes and hackathons.
• People leadership: talent acquisition, coaching and mentoring team
• Ensure the security and privacy of sensitive data used in analytics solutions, and comply with relevant regulations such as GDPR
• Participate in research projects aimed at advancing the field of data science and analytics, and presenting findings at conferences or publications. Institutionalize best practices, contribute to research and experimentation efforts.
• Represent the firm at industry events, conferences, and workshops, presenting research findings and sharing best practices with other experts in the field.

Education, Technical Skills & Other Critical Requirement:

• 6-12 years of relevant experience in AI/ analytics product & solution delivery
• Bachelor’s/Master’s degree in an information technology/computer science/Statistics/ Economics or equivalent fields experience.
• Strong understanding of Machine Learning and Deep Learning concepts, with a focus on Natural Language Processing.
• Proficiency in Python programming language, with experience using libraries like PyTorch for deep learning tasks.
• Familiarity with Elastic stack (Elasticsearch, Logstash, Kibana) for data management and analysis.
• Experience in optimizing algorithms and time series forecasts.
• Knowledge of prompt engineering techniques to improve model performance.
• Ability to prototype applications using Streamlit or similar tools.
• Experience working with large and complex internal, external, structured and unstructured datasets.
• Model development and deployment in cloud; Familiarity with Github, CI/CD process, Docker, Containerization & Kubernetes.
• Developing and maintaining detailed technical documentation.
• Solution Engineering and Consultative skills: Strong conceptual and creative problem-solving skills
• Familiarity with agile methodologies & tools.
• Good written, verbal communication skills and presentation skills; engage in meaningful manner with variety of audience: business stakeholders, technology partners & practitioners, executive and senior management.
• Industry knowledge about emerging AI trends, AI tools and technologies